Book Image

Managing Data Integrity for Finance

By : Jane Sarah Lat
Book Image

Managing Data Integrity for Finance

By: Jane Sarah Lat

Overview of this book

Data integrity management plays a critical role in the success and effectiveness of organizations trying to use financial and operational data to make business decisions. Unfortunately, there is a big gap between the analysis and management of finance data along with the proper implementation of complex data systems across various organizations. The first part of this book covers the important concepts for data quality and data integrity relevant to finance, data, and tech professionals. The second part then focuses on having you use several data tools and platforms to manage and resolve data integrity issues on financial data. The last part of this the book covers intermediate and advanced solutions, including managed cloud-based ledger databases, database locks, and artificial intelligence, to manage the integrity of financial data in systems and databases. After finishing this hands-on book, you will be able to solve various data integrity issues experienced by organizations globally.
Table of Contents (16 chapters)
1
Part 1: Foundational Concepts for Data Quality and Data Integrity for Finance
5
Part 2: Pragmatic Solutions to Manage Financial Data Quality and Data Integrity
10
Part 3: Modern Strategies to Manage the Data Integrity of Finance Systems

Preparing a sample data quality scorecard in Microsoft Excel

In the previous section, we discussed using data quality frameworks to get a better understanding of the quality of the data we are working with. In this section, we will discuss how to decide which metrics to use and create a sample template in Excel, then apply it to a fictional scenario for a company encountering issues with its data.

Establish the data quality metrics to be used

To prepare a data quality scorecard in Excel, we must first establish the data quality metrics that we will use. We covered them earlier in the chapter and we will create a sample scorecard that includes KPIs for completeness, accuracy, consistency, timeliness, and validity.

Define the scale for scoring KPIs

There are two options we can use when scoring the KPIs. It can either be qualitative or quantitative.

Scoring the KPIs qualitatively involves using the high, medium, and low criteria as follows:

  • High: The data receives...